{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T15:57:02Z","timestamp":1780588622545,"version":"3.54.1"},"reference-count":27,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,1,16]],"date-time":"2018-01-16T00:00:00Z","timestamp":1516060800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>HydroColor is a mobile application that utilizes a smartphone\u2019s camera and auxiliary sensors to measure the remote sensing reflectance of natural water bodies. HydroColor uses the smartphone\u2019s digital camera as a three-band radiometer. Users are directed by the application to collect a series of three images. These images are used to calculate the remote sensing reflectance in the red, green, and blue broad wavelength bands. As with satellite measurements, the reflectance can be inverted to estimate the concentration of absorbing and scattering substances in the water, which are predominately composed of suspended sediment, chlorophyll, and dissolved organic matter. This publication describes the measurement method and investigates the precision of HydroColor\u2019s reflectance and turbidity estimates compared to commercial instruments. It is shown that HydroColor can measure the remote sensing reflectance to within 26% of a precision radiometer and turbidity within 24% of a portable turbidimeter. HydroColor distinguishes itself from other water quality camera methods in that its operation is based on radiometric measurements instead of image color. HydroColor is one of the few mobile applications to use a smartphone as a completely objective sensor, as opposed to subjective user observations or color matching using the human eye. This makes HydroColor a powerful tool for crowdsourcing of aquatic optical data.<\/jats:p>","DOI":"10.3390\/s18010256","type":"journal-article","created":{"date-parts":[[2018,1,17]],"date-time":"2018-01-17T04:23:44Z","timestamp":1516163024000},"page":"256","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":106,"title":["The HydroColor App: Above Water Measurements of Remote Sensing Reflectance and Turbidity Using a Smartphone Camera"],"prefix":"10.3390","volume":"18","author":[{"given":"Thomas","family":"Leeuw","sequence":"first","affiliation":[{"name":"Sequoia Scientific, Inc., 2700 Richards Road, Suite 107, Bellevue, WA 98005, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emmanuel","family":"Boss","sequence":"additional","affiliation":[{"name":"School of Marine Sciences, University of Maine, 458 Aubert Hall, Orono, ME 04469, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,1,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7351","DOI":"10.1002\/2014GL061462","article-title":"Mapping atmospheric aerosols with a citizen science networks of smartphone spectropolarimeters","volume":"41","author":"Snik","year":"2014","journal-title":"Geophys. 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